Integrated, predictive vibration analysis of rotational machine within electronics rack

ABSTRACT

Predictive monitoring of a rotational machine of a cooling apparatus is provided by integrating a predictive vibration analyzer into an electronics rack being cooled by the cooling apparatus. The integrating includes associating at least one sensor of the predictive vibration analyzer with the rotational machine of the cooling apparatus. The analyzer includes a predetermined harmonics table of one or more base operational frequencies and associated rotational speed harmonics for the rotational machine indicative of one or more rotational faults, and the predictive vibration analyzer automatically evaluates vibration of the rotational machine during operation of the machine by analyzing vibration data therefor, and automatically ascertains, based on the vibration data, and the predetermined harmonics table, whether the rotational machine is predicted to possess a rotational fault of the one or more rotational faults.

BACKGROUND

Electrical power is conventionally supplied to a data processing systemby a power supply unit. A power supply unit is a component of a dataprocessing system that transforms, converts, or otherwise conditionselectrical power received from, for example, the power grid and providesthe transformed, converted, or conditioned electrical power to one ormore other components of the data processing system.

In one implementation, a data processing system may reside within one ormore racks, and may be, for example, a stand-alone computer processingsystem having high, mid or low-end processing capability. Power to anelectronics rack may be supplied by a bulk power assembly, whichincludes one or more bulk power regulators. As circuit densitiescontinue to increase at all levels of packaging, and there is anever-growing need for providing more power to, for instance, anelectronics rack comprising one or more electronic subsystems, there isan ever-growing need for continuous cooling of the bulk power assembly.As one solution, a cooling apparatus may be provided comprising one ormore bulk power fan assemblies associated with the bulk power assemblyfor air-cooling the power assembly.

Additionally, as is known, operating electronic devices produce heat.This heat should be removed from the devices in order to maintain devicejunction temperatures within desirable limits. Failure to remove heatcan result in increased device temperatures, potentially leading tothermal runaway conditions. To address this need, an electronics rackmay include one or more further cooling apparatuses, which facilitateair-cooling and/or liquid-cooling of one or more electronic devices orcomponents within the electronics rack.

BRIEF SUMMARY

Briefly summarized, provided herein in one aspect, is a method whichincludes: integrating a predictive vibration analyzer into anelectronics rack, the integrating comprising associating at least onesensor of the predictive vibration analyzer with a rotational machine,of a cooling apparatus to cool one or more components of the electronicsrack, to generate vibration data therefor, the predictive vibrationanalyzer comprising a predetermined harmonics table of one or more basefrequencies of vibration and associated harmonics for the machineindicative of one or more rotational faults therein; and evaluating, bythe predictive vibration analyzer, vibration of the rotational machineduring operation thereof by analyzing the vibration data, andautomatically ascertaining based thereon, and based on the predeterminedharmonics table, whether the rotational machine is predicted to possessa rotational fault of the one or more rotational faults.

In another aspect, a cooled electronic system is provided which includesan electronics rack comprising one or more electronic components to becooled, and a cooling apparatus integrated within the electronics rackfacilitating cooling of the one or more electronic components of theelectronics rack. The cooling apparatus includes a rotational machine,and a predictive vibration analyzer associated with the rotationalmachine for facilitating predictive monitoring of operation of therotational machine for one or more rotational faults. The predictivevibration analyzer includes: a predetermined harmonics table of one ormore base frequencies of vibration and associated harmonics for therotational machine indicative of one or more rotational faults therein;at least one sensor coupled to the rotational machine to generatevibration data therefor during operation of the rotational machine; anda control monitor programmed to evaluate the vibration data sensed fromthe rotational machine during operation thereof, and to automaticallyascertain based thereon, and based on the predetermined harmonics table,whether the rotational machine is predicted to possess a rotationalfault of the one or more rotational faults.

In a further aspect, a computer program product for predictivelyevaluating a rotational machine of a cooling apparatus to providecooling to an electronics rack is provided. The computer program productincludes a computer-readable storage medium readable by a processor andstoring instructions for execution by the processor to perform a method.The method includes: storing a predetermined harmonics table of one ormore base frequencies of vibration and associated harmonics for therotational machine indicative of one or more rotational faults therein;and monitoring vibration of the rotational machine during operationthereof by evaluating vibration data therefor within the electronicsrack, and automatically ascertaining based thereon, and based on thepredetermined harmonics table, whether the rotational machine ispredicted to possess a rotational fault of the one or more rotationalfaults.

Additional features and advantages are realized through the techniquesof the present invention. Other embodiments and aspects of the inventionare described in detail herein and are considered a part of the claimedinvention.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

One or more aspects are particularly pointed out and distinctly claimedas examples in the claims at the conclusion of the specification. Theforegoing and objects, features, and advantages of one or more aspectsof the invention are apparent from the following detailed descriptiontaken in conjunction with the accompanying drawings in which:

FIG. 1 is an elevational depiction of one embodiment of an electronicsrack to incorporate therein a predictive vibration analyzer, inaccordance with one or more aspects of the present invention;

FIG. 2 is a block diagram representation of one embodiment of anAC-to-DC power supply assembly, comprising a bulk power assembly and aframe controller for an electronics rack such as illustrated in FIG. 1,in accordance with one or more aspects of the present invention;

FIG. 3 is a representation of one embodiment of a bulk power fanassembly such as illustrated in FIG. 2, for which predictive vibrationanalysis may be provided, in accordance with one or more aspects of thepresent invention;

FIG. 4 is a cross-sectional elevational view of one embodiment of abearing assembly for an air-moving device, such as the bulk power fanassembly of FIG. 3, for which predictive vibration analysis is provided,in accordance with one or more aspects of the present invention;

FIGS. 5A & 5B depict different examples of a predetermined harmonicstable of base frequencies of vibration and associated rotational speedharmonics for a rotational machine, such as a bulk power fan assembly,to be dynamically evaluated, in accordance with one or more aspects ofthe present invention;

FIG. 6 is an exemplary graph plotting power spectrum density (PSD)acceleration (or amplitude) versus frequency for one bulk power fanassembly, and illustrates amplitude spikes in different x, y, and zdirections or channels indicative of one or more rotational faults to bepredictively identified, in accordance with one or more aspects of thepresent invention;

FIG. 7 is a flowchart of one embodiment of real-time, continuouspredictive failure analysis of a rotational machine of a coolingapparatus within an electronics rack being provided, in accordance withone or more aspects of the present invention;

FIG. 8 is a block diagram of one embodiment of a predictive vibrationanalyzer to be integrated into an electronics rack by in associationwith a rotational machine of a cooling apparatus, such as a bulk powerfan assembly, in accordance with one or more aspects of the presentinvention;

FIGS. 9A-9C depict one embodiment of a process for real-time evaluation,by a predictive vibration analyzer, of vibration data obtained for arotational machine of a cooling apparatus within an electronics rack, inaccordance with one or more aspects of the present invention;

FIG. 10 depicts an example of a peak amplitude table, automaticallyconstructed by a predictive vibration analyzer during evaluation of arotational machine, and which is useful in accordance with the processflow of FIGS. 9A-9C, in predicting whether the rotational machinepossess a rotational fault of one or more rotational faults identifiedin a predetermined, static harmonics table (such as depicted in FIGS. 5A& 5B), in accordance with one or more aspects of the present invention;and

FIG. 11 depicts one embodiment of a computer program productincorporating one or more aspects of the present invention.

DETAILED DESCRIPTION

As used herein, the term “electronics rack” includes any housing, frame,rack, compartment, blade server system, etc., having one or morecomponents of a data processing system or electronic system, and may be,for example, a stand-alone computer processing system having high, midor low end processing capability. An electronics rack may comprise atleast one electronic subsystem. An “electronic subsystem” refers to anysub-housing, blade, book, drawer, node, compartment, etc., having one ormore electronic components disposed therein. Each electronic subsystemof an electronics rack may be movable or fixed relative to the rack,with the electronics drawers of a multi-drawer rack unit and blades of ablade center system being two examples of electronic subsystems of anelectronics rack.

FIG. 1 depicts one embodiment of an electronics rack 100 with aplurality of electronic subsystems 101. In the embodiment illustrated,electronic subsystems 101 are air-cooled by cool air 102 ingressing vialouvered air inlet door 110, and exhausting out louvered air outlet door111 as hot air 103. One or more air-moving devices 109 within electronicsubsystems 101 may be provided to facilitate airflow through one or moreof the individual electronic subsystems 101 as part of the coolingapparatus provided within electronics rack 100. Electronics rack 100also includes at least one bulk power assembly 104 of an AC-to-DC powersupply assembly. AC-to-DC power supply assembly further includes, in oneembodiment, a frame controller, which may be resident in the bulk powerassembly 104 and/or in one or more electronic subsystems 101. Eachelectronic subsystem 101 includes, in one example, one or moreprocessors and associated memory. Also illustrated in FIG. 1 is one ormore input/output (I/O) drawer(s) 105, which may also include a switchnetwork. I/O drawer(s) 105 include, for example, PCI card slots and diskdrivers for the electronics rack.

In implementation, a three-phase AC source feeds power via an AC powersupply line cord 106 to bulk power assembly 104, which transforms thesupplied AC power to an appropriate DC power level for output viadistribution cable 107 to the plurality of electronic subsystems 101 andI/O drawer(s) 105. AC power supply line cord 106 supplies, in oneexample, three phases for international 415 V.sub.RMS, and has a currentlimit rating, for example, of 100 amps. The number of electronicsubsystems installed in the electronics rack is variable and depends oncustomer requirements for a particular system. Further, as explainedbelow, the number of bulk power regulators within each bulk powerassembly of the AC-to-DC power supply assembly is also variable and isdetermined, in one implementation, by the number of electronicsubsystems installed in the electronics rack, or more particularly, bythe power requirements of the common load of the electronics rack beingfed by the AC-to-DC power supply assembly.

FIG. 2 illustrates one example of an AC-to-DC power supply assembly 200comprising a frame controller 201 and a bulk power assembly 104, whichin this example comprises three single-phase bulk power regulators 220(labeled BPR1, BPR2 & BPR3). A serial communications bus 210 allowscommunication between frame controller 201 and bulk power regulators 220of bulk power assembly 104. The three-phase AC source is input 106 tobulk power assembly 104, and bulk power assembly 104 outputs 107 DCpower to a common load. In one typical electronics rack example, 350volts DC power is output to the common load of the rack from the bulkpower assembly.

As illustrated in FIG. 2, cooling of the bulk power assembly isaccomplished, in one embodiment, via one or more bulk power fanassemblies 225, which facilitate moving air through bulk power assembly104 from the air inlet side to the air outlet side of the electronicsrack. In addition to the one or more bulk power fan assemblies 225, acooling apparatus may be provided within the rack for cooling othercomponents of the rack. This cooling apparatus may include one or moreair-moving devices within the individual electronic subsystems, such asair-moving devices 109 within the electronic subsystems 101 ofelectronics rack 100 of FIG. 1. Alternatively, or in addition, theelectronics rack cooling apparatus may include a liquid-cooling featurefor cooling one or more components, such as one or more electroniccomponents within the electronics rack. For instance, in addition to oneor more air-moving devices within the individual electronic subsystems,selected electronic components may be directly or indirectlyliquid-cooled.

As one example, one or more processor modules may be indirectly cooledvia one or more liquid-cooled cold plates or heat sinks coupled thereto,in which case, the cooling apparatus also comprises a coolant loopcoupled to the liquid-cooled heat sink(s) and a coolant distributionsubsystem for facilitating liquid coolant flow through the one or moreliquid-cooled heat sinks. The coolant distribution subsystem may includeone or more coolant pumps in fluid communication with the coolantflowing through the coolant loop to facilitate movement of coolantthrough the coolant loop. Such a coolant pump is another example of arotational machine, which may be advantageously monitored within theelectronics rack for predicting a rotational fault therein, inaccordance with one or more aspects of the present invention.

Thus, a rotational machine, as used herein, may comprise a rotationalmachine that is part of an air-cooling or a liquid-cooling apparatus foran electronics rack. As one detailed example, the bulk power fanassembly 225 of FIG. 2 is discussed hereinbelow in greater detail. Thoseskilled in the art will note, however, that the concepts presented arereadily applicable to any rotational machine of a rack coolingapparatus, whether an air-cooling rotational machine, or liquid-coolantpump, for advantageously, predictively evaluating whether the machinepossesses a rotational fault, either at time of manufacture, before theproduct is shipped, or at a future time, for example, during normaloperation of the rotational machine within the electronics rack.

In order to facilitate continuous operation of a data processing systemwithin, or part of, an electronics rack, the cooling apparatus of theelectronics rack should be able to provide continuous cooling for anyspecified number of power on days of the data processing system. Inpractice, a failing rotational machine within a cooling apparatus couldresult in interruption of operation of the data processing system. Forinstance, a failing bulk power fan assembly, or more particularly, afailing fan bearing assembly of such a fan or blower, could result in aninterruption of operation, or at a minimum, degradation in performance,of the rack's data processing system. Currently, a failing rotationalmachine within a rack might be subjectively detected by an operatorhearing an audible change in operation of the rotational machine. Forexample, a failing bulk power fan assembly could generate excessivenoise. Depending on the implementation, with continuous power on days inthe range of 50-300, an approximate 10% failure rate might beexperienced in the bulk power fan assemblies. Provided herein thereforeis a predictive vibration analyzer and analysis method designed to beintegrated into the electronics rack to provide a real-time mechanism topredictably monitor for rotational machine failure, such as bearingfailure, within the rack.

By way of further explanation, FIG. 3 depicts a block diagram of oneembodiment of a bulk power fan assembly 225. In the embodiment shown,bulk power fan assembly 225 includes a motor 300, a ball-bearingassembly 301, and multiple rotating blades 302. FIG. 4 depicts oneembodiment of ball-bearing assembly 301 for an air-moving device such asbulk power fan assembly 225 of FIG. 3. As shown, ball-bearing assembly301 includes, in one embodiment, an outer ring 400 and an inner ring 401spaced apart to accommodate a cage 402, within which steel balls 403reside. A metallic shield 404 couples the outer and inner rings 400,401, and facilitates enclosing the ball-bearings 403 and a lubricant,such as a grease or oil, within the bearing assembly.

A root cause of rotational machine bearing failure, such as a fanassembly bearing failure, may be a high axial load on the bearing. Forinstance, double the specified loading could reduce bearing life by asmuch as 75%. A higher axial loading induces a deeper false brinelling.“False brinelling” is damage caused by fretting, with or withoutcorrosion, which causes imprints that look similar to brinelling, butare caused by a different mechanism. Brinell damage is characterized bypermanent material deformation (without loss of material), that occursduring one load event, whereas false brinelling is characterized bymaterial wear or removal, and occurs over an extended time fromvibration and light loads. A basic cause of false brinelling is that thedesign of the bearing does not have a method for redistribution oflubricant without large rotational movement of all bearing surfaces inthe raceway. Lubricant is pushed out of a loaded region during smalloscillatory movements and vibration, where the bearing surfacesrepeatedly do not move very far. Without lubricant, wear is increasedwhen the small oscillatory movements occur again. It is possible for theresulting wear and debris to oxidize and form an abrasive compound,which further accelerates wear.

A lower axial load, that is, less bearing spring compression, generallyresults in longer operational life than a bearing assembly under ahigher axial load, which tends to induce deeper false brinelling, andearlier failure potential.

Disclosed herein is the integration of predictive vibration analysisinto an electronics rack to provide an early warning, either at themanufacturer, or at a customer site, of a future rotational machinefailure based, for instance, on undesirable vibration of the rotationalmachine resulting from dents or false brinelling of, for instance, oneor more components of a bearing assembly of the rotational machine.

Given a bearing assembly type and a specified rotational speed ofoperation, transformed to frequency, amplitude of vibration caused byball-bearing revolution is able to be detected by experimentallyanalyzing the rotating machinery vibration signal. For instance, manualevaluation of operational vibrational signals may be employed inexperimentally constructing a static harmonics table such as describedbelow. When a ball, or an inner-ring or outer-ring, such as illustratedin FIG. 4, deform (or dent), the amplitude of the ball revolutionincreases, and there will be additional vibration caused by such aninner-ring dent, outer-ring dent and/or ball-bearing dent. This manualor experimental vibration analysis can be performed by one of ordinaryskill in the art using, in part, one or more existing formulas forball-bearing assemblies, such as:

$\begin{matrix}{{{Vibration}\mspace{14mu} {caused}\mspace{14mu} {by}\mspace{14mu} {ball}\mspace{14mu} {{revolution}{\mspace{11mu} \;}({fa})}} = {\frac{1}{2}\left( {1 - {\frac{D_{w}}{D_{pw}}\cos \mspace{14mu} {\alpha 0}}} \right){fr}}} & (1) \\{{{Vibration}\mspace{14mu} {caused}\mspace{14mu} {by}\mspace{14mu} {retainer}\mspace{14mu} {rotation}\mspace{14mu} ({fb})} = {\frac{1}{2}\left( {1 - {\frac{D_{w}}{D_{pw}}\cos \mspace{14mu} {\alpha 0}}} \right){fr}}} & (2) \\{{{Vibration}\mspace{14mu} {caused}\mspace{14mu} {by}\mspace{14mu} {ball}\mspace{14mu} {{rotation}{\mspace{11mu} \;}({fc})}} = {\frac{1}{2}\left( {\frac{D_{pw}}{D_{w}} - {\frac{D_{w}}{D_{pw}}{\cos \;}^{2}\mspace{11mu} {\alpha 0}}} \right){fr}}} & (3) \\{\mspace{85mu} {{{Vibration}\mspace{14mu} {caused}\mspace{14mu} {by}\mspace{14mu} {ball}\mspace{14mu} {pass}\mspace{14mu} ({fd})} = \left( \frac{Zfa}{Z\left( {{fr} - {fa}} \right)} \right)}} & (4) \\{\mspace{85mu} {{{Vibration}\mspace{14mu} {caused}\mspace{14mu} {by}\mspace{14mu} {dents}\mspace{14mu} {or}\mspace{14mu} {bumps}\mspace{14mu} ({fe})}:}} & (5) \\{\mspace{85mu} {{{Vibration}\mspace{14mu} {in}\mspace{14mu} {Axial}\mspace{14mu} {{direction}{\mspace{11mu} \;}({fet})}} = {{nZ}\left( {{fr} - {fa}} \right)}}} & (5.1) \\{\mspace{85mu} {{{Vibration}\mspace{14mu} {in}\mspace{14mu} {Radial}\mspace{14mu} {{direction}{\mspace{11mu} \;}({fer})}} = {{fet} \pm {fr}}}} & (5.2)\end{matrix}$

From, at least in part, the above-noted Equations, one skilled in theart can ascertain:

Vibration caused by outer ring raceway dents or bumps (ff)=nZf  (6)

Vibration caused ball surface dents or bumps (fg):  (7)

Vibration in Axial direction (fgt)=2nfc  (7.1)

Vibration in Radial direction (fgr)=fgt±fa  (7.2)

wherein:

-   -   Dw=Ball diameter (mm);    -   Dpw=Pitch circle diameter (mm);    -   α0=Nominal contact angle)(°);    -   Z=Number of balls;    -   n=Integer number;    -   fr=Inner-ring rotation speed (Hz); and    -   Fr=Outer-ring rotation speed (Hz).

FIGS. 5A & 5B depict examples of two static harmonics tables which maybe obtained, or predefined, for a particular rotational machine type foruse in predictive analysis of operation of the rotational machine. Forinstance, the table(s) may be constructed for a particular type ofbearing assembly of a cooling apparatus, which is operating at the samespeed. Note that in the Table 1 & 2 examples of FIGS. 5A & 5B, therotational machine comprises an air-moving device (or blower) for, forinstance, a bulk power assembly. In the case of Table 1, the blower isspecified to operate at 1900 RPMs, while in Table 2, the blower speed is2000 RPMs. Otherwise, the bearing assembly characteristics, such as theball diameter, number of balls, nominal contact angle, outer referencediameter, inner reference diameter, and pitch circle diameter, etc., arethe same. Note that different frequencies for the inner-ring rotationalspeed, ball revolution, retainer rotation, ball rotation, and ballpaths, may be obtained. Using known equations, such as the above-notedEquations (1)-(7.2), one of ordinary skill in the art can ascertain basevibration frequency values for any inner-ring raceway dents, outer-ringraceway dents, ball surface dents, etc., as illustrated in the Tables.Note that the left-most column for the inner-ring raceway dents,outer-ring raceway dents, and ball surface dents refers to the basefrequency of vibration, and the columns to the right refer to harmonicfrequencies corresponding to the respective base frequency. Tables 1 & 2are examples of predetermined harmonics tables of one or more basefrequencies and associated rotational speed harmonics for the rotationalmachine that may be indicative of one or more rotational faults withinthe machine. In this example, the one or more rotational faults couldcomprise one or more dents in the inner-ring raceway, outer-rightraceway and/or ball surface of the bearing assembly. These predeterminedharmonics tables are referred to herein as static tables since they arepredefined or predetermined for exemplary faults, referred to herein asrotational faults, in the bearing assembly.

FIG. 6 is a graph of one embodiment of vibration data sampled from abulk power fan assembly bearing, with an operational rating of 1900revolutions per minute (RPM). In this graph, vibrations are plottedbetween sampled frequencies of 10 and 1000 Hz, along with arepresentation of signal amplitude, such as power spectrum density (PSD)acceleration. As shown, vibration in each of three dimensions isplotted, that is, in x, y and z direction(s) or channel(s). As explainedfurther below, when a peak amplitude signal is identified in multipledirections or channels, a rotational fault may be, to a higherconfidence level, predicted to be present in the rotational machine.

Generally stated, provided herein is a predictive failure analyzer andanalysis method for real-time vibration monitoring and analysis of arotational machine within an electronics rack, such as a fan or pumpassembly of a cooling apparatus within or associated with theelectronics rack. The predictive failure analyzer and analysis methoddisclosed herein embodies a predictive process which is able to providean early warning of a rotational fault within a rotational machine ofthe cooling apparatus. In one implementation, the method includes:integrating a predictive vibration analyzer into an electronics rack,the integrating comprising associating at least one sensor of thepredictive vibration analyzer with a rotational machine, of the coolingapparatus to cool one or more components of the electronics rack, togenerate vibration data therefor, the predictive vibration analyzerincluding a predetermined harmonics table of one or more basefrequencies of vibration and associated rotational harmonics for therotational machine indicative of one or more rotational faults therein;and evaluating, by the predictive vibration analyzer, vibration of therotational machine during operation thereof by analyzing the vibrationdata, and automatically ascertaining based thereon, and based on thepredetermined harmonics table, whether the rotational machine ispredicted to possess a rotational fault of the one or more rotationalfaults.

By way of example, the one or more sensors of the predictive vibrationanalyzer may include one or more triaxial accelerometers, and theintegrating may include coupling the one or more triaxial accelerometersto the rotational machine to facilitate generating the vibration datatherefor. Note that in one example, the rotational machine comprises aball-bearing assembly, and is provided to facilitate movement of acoolant, such as air or a liquid coolant, within the electronics rack tofacilitate cooling of one or more components of the electronics rack.Note also, although referred to herein as a single rotational machine,the concepts presented may be readily applied to any number ofrotational machines of a cooling apparatus within an electronics rack.For instance, multiple rotational machines may be concurrently monitoredfor predictive vibration analysis, in accordance with one or moreaspects of the present invention disclosed herein.

In one embodiment, the predictive vibration analyzer is configured orprogrammed to automatically transform the vibration data to a pluralityof sample frequency signals with associated signal amplitudes in each ofthree directions, that is, in x, y, and z directions, and theautomatically ascertaining includes generating, from the plurality offrequency signals, a peak amplitude table of sample frequency signals ofthe plurality of sample frequency signals with peak amplitude values inone, or more, or all three of the x, y, and/or z directions.

By way of example, generating the peak amplitude table may include, fora selected frequency signal of the plurality of sample frequencysignals, determining whether the selected frequency signal has a peaksignal amplitude by comparing the associated signal amplitude of theselected frequency signal to an average signal amplitude for a window ofsample frequency signals, of the plurality of sample frequency signals,about the selected frequency signal, and determining whether theassociated signal amplitude of the selected frequency signal exceeds theaverage signal amplitude of the window of sample frequency signals by aset percentage. For instance, the set percentage may be predefined for aparticular rotational machine to be in a range of 150-200%. As onespecific example, the set percentage might be 175%.

In one implementation, generating the peak amplitude table may includeautomatically determining, by the predictive vibration analyzer, whetherto add the selected frequency signal to the peak amplitude table whenits associated signal amplitude exceeds the average signal amplitude forthe window by the predefined percentage. For instance, the automaticallydetermining may include ascertaining whether the peak amplitude tablealready contains, within a preset frequency range of the selectedfrequency signal, an existing peak amplitude value, and if so, onlysubstituting for the existing peak amplitude value the selectedfrequency signal's signal amplitude when that signal amplitude isgreater than the existing peak amplitude value in the table. Thisprocess may be repeated for the selected frequency signal in each of thex, y and z directions, in one embodiment.

By way of further example, the automatically ascertaining performed bythe predictive vibration analyzer may include referencing thepredetermined harmonics table and the peak amplitude table indetermining for a base frequency vibration in the predeterminedharmonics table a count of the number of harmonic frequencies of thebase frequency that are present in the peak amplitude table, and ifthree or more harmonic frequencies are present for the base frequencywithin a set frequency range, automatically predicting by the predictivevibration analyzer, that the rotational machine possesses the rotationalfault of the one or more rotational faults. In one embodiment, this mayinclude determining for the base frequency vibration a number ofdirections that the associated harmonic frequencies of the basefrequency are present in the peak amplitude table, and automaticallypredicting, by the predictive vibration analyzer, that the rotationalmachine possesses the rotational fault where associated harmonicfrequencies are present in multiple directions.

In one implementation, the determining of the count of the number ofharmonic frequencies in the peak amplitude table that are present foreach base frequency in the predetermined harmonics table may berepeated, and based thereon, the predictive vibration analyzer maydetermine whether the rotational machine possesses the rotational fault.

In a further implementation, where three or more harmonic frequenciesare identified in the peak amplitude table associated with a particularbase frequency, the predictive vibration analyzer may automaticallydetermine whether the base frequency is also present in the peakamplitude table in each of the x, y, and z directions, and if so,automatically indicate that the rotational machine possesses or willpossess the rotational fault.

Disclosed herein is a real-time, continuous vibration analysis approachfor monitoring a rotational machine, such as an air-moving device orcoolant pump within an electronics rack, to detect (for instance) earlyball-bearing failure. The predictive vibration analyzer disclosedcomprises, in one embodiment, one or more accelerometers or sensors,along with certain data processing of sent signals, and an algorithm toperform vibration analysis FFT (Fast Fourier Transform), as well as aprocess to compare a table of known bearing vibration values andball-bearing frequencies. The analyzer is programmed to determine earlyball-bearing failure potential in real-time. Increases in amplitude ofvibration caused by a ball revolution due to a defect are ascertained,along with additional vibration data caused by inner-ring dents,outer-ring dents, and ball-bearing dents. Analysis is performed inreal-time and continuously to compare the previously collected data tothe currently obtained data to ensure that there has been no significantchange in ball-bearing operation.

In one implementation, an integrated microprocessor and triaxialaccelerometer(s) are provided coupled to the rotational machine toobtain and analyze vibration signals from the machine in order toprovide predictive failure detection. The analysis approach describedherein advantageously finds peaks using a rolling frequency average fora specified frequency range; thus, identifying peaks relative to arolling background average. The found peak frequencies are compared tofrequencies related to bearing failure mechanisms' harmonic frequencies,depending on the operational RPMs of the machine. The bearing failurefrequencies may be caused by ball revolution defect, and/or inner-ringdents, outer-ring dents, etc., of the bearing assembly. Analysis isperformed in real-time, and continuously, comparing current obtainedfrequencies with previously collected data to ensure that there has beenno significant change in ball-bearing behavior.

Advantageously, the approach described herein may be employed for aninitial predictive screening of a rotational machine of the coolingapparatus prior to shipping of any product incorporating the device, aswell as post-shipping, to automatically signal, for instance, a controlsystem, of an impending operational problem with the bearing assembly ofthe rotational machine.

FIG. 7 is an overview of one embodiment of a process for predictivelymonitoring one or more rotational machines of a cooling apparatusassociated with an electronics rack. The process includes integrating apredictive vibration analyzer into the electronics rack by coupling oneor more sensors of the analyzer to one or more rotational machines ofthe cooling apparatus within the electronics rack 700. This may beaccomplished, in one embodiment, by physically integrating the one ormore sensors into, for instance, the bearing assembly of one or morerotational machines within the rack. By way of example, the one or moresensors may comprise accelerometers, such as triaxial accelerometers,which provide three-dimensional vibration data. A predeterminedharmonics table is obtained for the rotational machine by, for example,measuring base vibration frequencies, and calculating therefromcorresponding harmonic frequencies for various faults in the rotationalmachine, such as one or more of the above-described bearing assemblyfaults 710. Note that, in one embodiment, the predetermined harmonicstable may be stored within memory of the predictive vibration analyzerfor a particular operational speed of the rotational machine, havingbeen predetermined or predefined experimentally as described above, andremaining substantially static for use as a reference in making thepredictive determinations described herein. The rotational machine(s) ofthe cooling apparatus is then operated at its intended or specifiedoperational speed 720, and the predictive vibration analyzercontinuously (e.g., periodically) samples vibration data from thesensor(s) coupled to the rotational machine, and automaticallyascertains therefrom, and based on the predetermined harmonics table,whether operation of the rotational machine(s) has change and is nowpredicted to possess a rotational fault 730. Depending on theimplementation, output in the form of a signal may be provided to, forinstance, a system controller within the electronics rack, or even to acontroller remote from the electronics rack, indicative of whether arotational fault in the rotational machine has been predicted 740.

FIG. 8 is a block diagram of one embodiment of a predictive vibrationanalyzer, generally denoted 800, to be incorporated into an electronicsrack. In the depicted embodiment, predictive vibration analyzer 800includes one or more processors 810, such as one or moremicroprocessors, a memory 820 (e.g., main memory), and one or moreinput/output (I/O) devices 830, coupled to one another via, forinstance, one or more busses 801 and/or other connections. Thepredictive vibration analyzer further includes one or more vibrationsensors, such as one or more accelerometers 840, coupled via theinput/output device(s) 830 to the processor and memory. Theaccelerometer(s) may include or be a triaxial accelerometer(s), whichprovides time-dependent vibration data in x, y, and z directions. In oneimplementation, the accelerometer(s) is integrated into (for instance,attached to) one or more components of the rotational machine (e.g.,bearing assembly) under analysis, in order to provide the vibrationdata.

As illustrated in FIG. 8, processor 810 executes fault prediction logic812, such as depicted below in connection with FIGS. 9A-9C, and memory820 includes (in addition to the fault prediction logic instructions)one or more tables or data structures, such as the predeterminedharmonics table and peak amplitude tables described herein.

Note that, in one implementation, the predictive vibration analyzercould comprise a hardware component, such as a micro-electromechanicalsystem (MEMS), programmed to accomplish the processing disclosed herein.As one specific example, the MEMS could comprise an analog device, suchas an ADXL326 component. The input voltage, data collection andconversion may be implemented, in one embodiment, in a motor driveassembly (MDA) of the rotational machine. The processor (ormicroprocessor) employed may be programmed to advantageously performs aFast Fourier Transform of the sensed time-dependent vibration signalsobtained from the accelerometers into sample frequency data, forprocessing as described herein.

FIGS. 9A-9C depict one embodiment of predictive analysis processing, inaccordance with one or more aspects of the present invention. In thesefigures, FIG. 9A depicts a main, overview process flow, FIG. 9B depictsa peak amplitude detection process, and FIG. 9C depicts one embodimentof peak check processing. The processes are divided into blocks tofacilitate a discussion of the flow presented.

Beginning with FIG. 9A, Block A, the predictive vibration analyzeracquires raw vibration data from one or more accelerometers andautomatically transforms the data using, for instance, a Fast FourierTransform (FFT) into frequency domain to provide a plurality of samplefrequency signals 900. In one implementation, the FFT may be saved inmemory of the predictive vibration analyzer.

In Block B, a call is made to a sub-process to build tables of signalamplitude peaks for x, y, and z directions 902, referred to herein asthe peak amplitude tables. One embodiment of this process is outlined inFIG. 9B, and an example of one embodiment of a peak amplitude table isdepicted in FIG. 10.

Referring to FIG. 9B, in Block G, an empty peak data table isinitialized 936, and used to contain sample frequency and signalamplitude data. Processing starts to step through each sample frequencyand associated amplitude entry in the vibration data obtained by thepredictive vibration analyzer 938. Note that in the example of FIG. 9B,the initialization for the outer processing loop is for the processes ofBlocks H-L, outlined in the figure. A current or selected frequencysignal and associated signal amplitude are obtained from the vibrationdata 940. Note that this process is repeated for each of the threechannels (or directions), x, y, and z. Generally, in Block I, processingdetermines a window of vibration signal data within a set frequencyrange about the selected frequency signal. The frequency window may bedetermined during product development, and may be, for instance, −5 Hzto +5 Hz of the selected frequency signal. Once a window of samplefrequency signals is determined, an average signal strength for thatwindow can be found. Note that the window may range from +/−0 Hz to+/−the set frequency window (such as 5 Hz), but is a minimum of half thefrequency window.

In particular, in Block I, processing searches the vibration databackwards from the selected frequency signal, minus a preset range, suchas 5 Hz, bounded by the initial vibration data frequency, to determine alower window edge 942, and a window start variable is set to this lowerdata position 944. A similar process occurs for the upper windowboundary in that the vibration data is searched forward from theselected frequency to, for instance, signal +5 Hz, bounded by the higherend of the vibration data, to determine the upper window edge 946, and awindow end variable is set to the higher window boundary 950. Once thewindow is ascertained about the selected frequency signal, then datastrength within the window is summed to determine a sum of the signalstrength within the window 952. A threshold variable is defined as thesum of the vibration data divided by the size of the window, times apreset percentage, such as 1.75 954, as illustrated in Block J. Thepreset percentage may be determined during product development for aparticular rotational machine. An amplitude signal for the selectedfrequency signal over this associated threshold value above the averagewindow signal strength is determined to be an amplitude peak 956.

In Block K, assuming that a peak amplitude value has been identified,processing determines whether there is an existing peak amplitude valuein the corresponding peak amplitude table within a set frequency range958. If the frequency is not found in the peak amplitude table 959, thenthe new frequency and associated signal strength are added to the table964. If the new amplitude signal is greater than such an existing peakamplitude signal in the table 960, then the peak amplitude table isupdated with the new signal peak at the current, selected frequencysignal 962. Otherwise, processing continues in Block L by determiningwhether all frequency signals in the vibration data have been processed966, and if “no”, returns to obtain a next selected frequency signal andassociated amplitude value for processing 940. Once all sample frequencysignals in the vibration data have been processed, the peak amplitudetable is complete, and output (for instance, stored in memory) 968, andprocessing returns to the point of sub-routine call. Note that the peakdata table contains the frequency signals with the highest signalamplitudes within the rolling frequency windows.

Returning to the process flow of FIG. 9A, once the peak amplitude tablesare constructed 902, processing references in Block C the static,predetermined harmonics table of one or more base frequencies ofvibration and associated rotational harmonics for the rotational machineindicative of one or more rotational faults therein 903 (predeterminedas described above), and initializes, for each base frequency in theharmonics table 904, an input table of the sample vibration data, toloop through Blocks D-F of the process illustrated.

In Block D, the harmonic frequencies in the predetermined harmonicstable are checked to determine, for each base frequency, a number ofharmonic frequencies that are present, and in how many channels. Outputfrom this block is a count of amplitude peaks within a frequency windowof each harmonic frequency that are present. In particular, in Block D,a peak harmonic count variable is initialized 906, and for each harmonicin the predetermined harmonics table 908, processing performs the peakcheck process 910 depicted, in one embodiment, in FIG. 9C.

The process of FIG. 9C uses the peak amplitude table(s) built in FIG.9B, and a selected input (or base frequency) to determine if there is apeak signal in the peak amplitude table within a set frequency range ofthe selected frequency. In one example, the set range may bepredetermined during product development, and may be, for instance, in arange of 5 Hz to 10 Hz, such as 7 Hz. In Block M of FIG. 9C, the windowrange is defined by a low window variable set to the input frequency −7Hz 970, and a high window variable set to the input frequency +7 Hz 972.Additionally, a peak channel count variable is initialized to zero 974.

In Block N, the depicted processing is repeated for each x, y, and zchannel or direction. Processing inquires whether the current peak is inthe frequency window of the input frequency signal in one direction, andif “yes”, then the number of failed or peak directions for this inputfrequency signal is incremented, and processing exits the sub-loop tocheck data for a next direction or channel. The process repeats for eachpeak table entry in a given channel.

In particular, as illustrated in Block N, processing steps through thepeak amplitude table for a given channel 976, and determines whether thesignal frequency in the table for this channel is greater than the lowwindow variable 978. If “yes”, then processing determines whether thesignal frequency is less than the high window variable 980. If “yes”again, then the peak channel count is incremented 982. Otherwise, if thecurrent frequency signal is outside of the window, processing determineswhether all entries in the peak amplitude table have been processed 984,and if “no”, returns to process a next entry in the table. Once allentries in a peak amplitude table for a particular direction or channelare complete, processing determines whether all channels have beenevaluated 986. If “no”, then processing loops back to obtain peakamplitude data for a next direction or channel.

Once all directions have been processed, then in Block O, processingdetermines whether the peak channel count is greater than 1 988, thatis, have two or more channels failed (i.e., been identified with peaks).If “yes”, then the failing peak channel count is returned 990,otherwise, a zero value is returned 992, and processing returns 994 tothe flow of FIG. 9A.

Returning to the process of FIG. 9A, once the peak amplitude tables havebeen checked for harmonics, processing determines whether the returnedpeak check variable indicates a non-zero fail condition 912, and if“yes”, then a total failed harmonic count variable is incremented 914.Processing then determines whether all harmonics in the predeterminedharmonics table have been processed 916, and if “no”, returns to processa next harmonic in the table, with reference to the sub-process of FIG.9C.

In Block E, processing determines whether three or more harmonicfrequencies for a given base frequency have been identified in the peakamplitude tables 918, and if three or more are present, proceeds (in oneexample) to the processing of Block F, otherwise continues to check anext base frequency for harmonics. In particular, as illustrated inBlock E, processing determines whether the total failed harmonic countexceeded two, that is, have at least three harmonics been identified918, and if “no”, determines whether all base frequencies in thepredetermined harmonics table have been considered 920, and if “no”again, returns to consider harmonics for a next base frequency.

Assuming that three or more harmonics have been identified, thenprocessing determines in Block F whether a warning or fail conditionshould be immediately issued based, in one example, on consideration ofthe base frequency itself. In particular, processing determines whetherbase frequency checking is enabled 924, and if “no”, sends a fail outputlevel to, for instance, the motor drive assembly, for corrective action,and/or signals a controller remote from the predictive vibrationanalyzer to initiate operator action to service the rotational machine930. Assuming that the base frequency checking is enabled, then for thebase frequency, the peak check sub-processing of FIG. 9C is initiated926, and processing determines whether a base frequency peak has beenidentified in all three channels, that is, in the x, y, and z directions928. If “yes”, then the fail output signal is sent, otherwise (in oneembodiment), a warning output level signal 932 may be sent to, forinstance, the motor drive assembly associated with the rotationalmachine. After sending the signals, processing determines whether allentries in the predetermined harmonics table have been considered, andif “yes”, completes the current process flow 922, which as noted, may berepeated periodically in a continuous manner during operation of therotational machine within the electronics rack.

FIG. 10 depicts one embodiment of a peak amplitude signal table for x,y, and z directions, referred to in the table as the vertical,horizontal, and in/out directions, wherein the frequencies of theidentified peak signals are recorded along with the associated signalamplitudes for each of the directions. Note in the representativeexample provided in FIG. 10 that similar peak signals are identified inmultiple channels or directions for a given frequency signal. In thosecases where the frequency signal has a peak in multiple directions, apotential failure may be predicted with confidence, in accordance withthe processing disclosed herein.

Advantageously, provided herein is a predictive vibration analyzer andanalysis approach, integrated with a rotational machine, such as abearing assembly of a cooling apparatus or component, within anelectronics rack. In accordance with the predictive failurealgorithm/analysis described above, a predicted failure of a rotationalmachine (e.g., bearing assembly) may be identified during testing at amanufacturer or during normal operation at, for instance, a customersite. Once identified, a preventive action may then be takenautomatically by the predictive vibration analyzer. See in this regard,the processes of FIGS. 7 & 9A, described above. For instance, once thepredictive vibration analyzer determines that there is a failing outputfor a bearing assembly, the analyzer may automatically initiate actionto limit damage to the bearing assembly and/or to surrounding componentswithin the electronics rack. For instance, the predictive vibrationanalyzer could automatically stop operation of the rotational machine,or modify operation of the rotational machine by, for instance, changingits speed of operation. As one example, if the rotational machine isspecified to operate at 1900 RPMs, then the predictive vibrationanalyzer could automatically change the speed of operation to, forinstance, 1800 RPMs, to possibly allow for continued operation of therotational machine at the reduced speed. As another example, eithercommensurate with automatic control of the rotational machine, or in thecase of outputting a warning, an operator could be automaticallysignaled to evaluate the results of the predictive vibration analyzer,and possibly take further action, such as to repair or replace therotational machine.

As will be appreciated by one skilled in the art, one or more aspects ofthe present invention may be embodied as a system, method or computerprogram product. Accordingly, one or more aspects of the presentinvention may take the form of an entirely hardware embodiment, anentirely software embodiment (including firmware, resident software,micro-code, etc.) or an embodiment combining software and hardwareaspects that may all generally be referred to herein as a “circuit,”“module” or “system”. Furthermore, one or more aspects of the presentinvention may take the form of a computer program product embodied inone or more computer readable medium(s) having computer readable programcode embodied thereon.

Referring to FIG. 11, in one example, a computer program product 1100includes, for instance, one or more non-transitory computer readablestorage media 1102 to store computer readable program code means, logicand/or instructions 1104 thereon to provide and facilitate one or moreembodiments.

The present invention may be a system, a method, and/or a computerprogram product. The computer program product may include a computerreadable storage medium (or media) having computer readable programinstructions thereon for causing a processor to carry out aspects of thepresent invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the block may occur out of theorder noted in the figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise” (andany form of comprise, such as “comprises” and “comprising”), “have” (andany form of have, such as “has” and “having”), “include” (and any formof include, such as “includes” and “including”), and “contain” (and anyform contain, such as “contains” and “containing”) are open-endedlinking verbs. As a result, a method or device that “comprises”, “has”,“includes” or “contains” one or more steps or elements possesses thoseone or more steps or elements, but is not limited to possessing onlythose one or more steps or elements. Likewise, a step of a method or anelement of a device that “comprises”, “has”, “includes” or “contains”one or more features possesses those one or more features, but is notlimited to possessing only those one or more features. Furthermore, adevice or structure that is configured in a certain way is configured inat least that way, but may also be configured in ways that are notlisted.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below, if any, areintended to include any structure, material, or act for performing thefunction in combination with other claimed elements as specificallyclaimed. The description of the present invention has been presented forpurposes of illustration and description, but is not intended to beexhaustive or limited to the invention in the form disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the invention.

1-11. (canceled)
 12. A cooled electronic system comprising: anelectronics rack comprising one or more electronic components to becooled; and a cooling apparatus integrated within the electronics rackfor facilitating cooling the one or more electronic components of theelectronics rack, the cooling apparatus comprising a rotational machine,and a predictive vibration analyzer associated with the rotationalmachine for facilitating predictive evaluation of operation of therotational machine, the predictive vibration analyzer comprising: apredetermined harmonics table of one or more base frequencies ofvibration and associated rotational harmonics for the rotational machineindicative of one or more rotational faults therein; at least one sensorcoupled to the rotational machine to generate vibration data thereforduring operation of the rotational machine; and a control monitorprogrammed to evaluate the vibration data sensed from the rotationalmachine during operation thereof, and to automatically ascertain basedthereon, and based on the predetermined harmonics table, whether therotational machine is predicted to possess a rotational fault of the oneor more rotational faults.
 13. The cooled electronic system of claim 12,wherein the at least one sensor comprises one or more triaxialaccelerometers coupled to the rotational machine to facilitategenerating the vibration data therefor.
 14. The cooled electronic systemof claim 12, wherein the control monitor automatically transforms thevibration data into a plurality of sample frequency signals withassociated signal amplitudes for use, in comparison with thepredetermined harmonics table, to facilitate the automaticallyascertaining whether the rotational machine is predicted to possess therotational fault of the one or more rotational faults.
 15. The cooledelectronic system of claim 14, wherein the control monitor automaticallygenerates, from the plurality of sample frequency signals, a peakamplitude table of sample frequency signals of the plurality of samplefrequency signals with peak amplitude values in at least one of an x, y,or z direction.
 16. The cooled electronic system of claim 15, whereingenerating the peak amplitude table of sample signal frequenciescomprises, for a selected frequency signal of the plurality of samplefrequency signals, determining whether the selected frequency signal hasa peak signal amplitude by comparing the associated signal amplitude ofthe selected frequency signal to an average signal amplitude for awindow of sample frequency signals, of the plurality of sample frequencysignals, about the selected frequency signal, and determining whetherthe associated signal amplitude of the selected frequency signal exceedsthe average signal amplitude for the window of sample frequency signalsby a set percentage.
 17. The cooled electronic system of claim 16,wherein generating the peak amplitude table further comprisesautomatically determining, by the predictive vibration analyzer, whetherto add the selected frequency signal to the peak amplitude table whenits associated signal amplitude exceeds the average signal amplitude forthe window by the defined percentage, the automatically determiningcomprising ascertaining whether the peak amplitude table alreadycontains, within a preset frequency range of the selected frequencysignal, an existing peak amplitude value, and if so, substituting forthe existing peak amplitude value the selected frequency signal's signalamplitude within the peak amplitude table when that signal amplitude isgreater than the existing peak amplitude value.
 18. The cooledelectronic system of claim 17, wherein the control monitor automaticallyrepeats the determining whether the selected frequency signal possessesa peak amplitude signal to evaluate the selected frequency signal ineach of the x, y, and z directions.
 19. The cooled electronic system ofclaim 15, wherein the control monitor of the predictive vibrationanalyzer automatically references the predetermined harmonics table andthe peak amplitude table in determining for a base frequency ofvibration in the predetermined harmonics table a count of a number ofharmonic frequencies of the base frequency that are present in the peakamplitude table, and if three or more harmonic frequencies are presentfor the base frequency within a set frequency range, automaticallypredicting, by the predictive vibration analyzer, that the rotationalmachine possesses the rotational fault of the one or more rotationalfaults.
 20. A computer program product for predictively evaluating arotational machine of a cooling apparatus to provide cooling to anelectronics rack, the computer program product comprising: acomputer-readable storage medium readable by a processor and storinginstructions for execution by the processor to perform a methodcomprising: storing a predetermined harmonics table of one or more basefrequencies of vibration and associated rotational harmonics for therotational machine indicative of one or more rotational faults therein;and monitoring vibration of the rotational machine during operationthereof by evaluating vibration data therefor within the electronicsrack, and automatically ascertaining based thereon, and based on thepredetermined harmonics table, whether the rotational machine ispredicted to possess a rotational fault of the one or more rotationalfaults.
 21. The computer program product of claim 20, wherein themonitoring automatically transforms the vibration data into a pluralityof sample frequency signals with associated signal amplitudes for use,in comparison with the predetermined harmonics table, to facilitate theautomatically ascertaining whether the rotational machine is predictedto possess the rotational fault of the one or more rotational faults.22. The computer program product of claim 21, wherein the monitoringautomatically generates, from the plurality of sample frequency signals,a peak amplitude table of sample frequency signals of the plurality ofsample frequency signals with peak amplitude values in at least one ofan x, y, or z direction.
 23. The computer program product of claim 22,wherein generating the peak amplitude table of sample signal frequenciescomprises, for a selected frequency signal of the plurality of samplefrequency signals, determining whether the selected frequency signal hasa peak signal amplitude by comparing the associated signal amplitude ofthe selected frequency signal to an average signal amplitude for awindow of sample frequency signals, of the plurality of sample frequencysignals, about the selected frequency signal, and determining whetherthe associated signal amplitude of the selected frequency signal exceedsthe average signal amplitude for the window of sample frequency signalsby a set percentage.
 24. The computer program product of claim 23,wherein generating the peak amplitude table further comprisesautomatically determining, by the predictive vibration analyzer, whetherto add the selected frequency signal to the peak amplitude table whenits associated signal amplitude exceeds the average signal amplitude forthe window by the defined percentage, the automatically determiningcomprising ascertaining whether the peak amplitude table alreadycontains, within a preset frequency range of the selected frequencysignal, an existing peak amplitude value, and if so, substituting forthe existing peak amplitude value the selected frequency signal's signalamplitude within the peak amplitude table when that signal amplitude isgreater than the existing peak amplitude value.
 25. The computer programproduct of claim 24, wherein the monitoring automatically repeats thedetermining whether the selected frequency signal possesses a peakamplitude signal to evaluate the selected frequency signal in each ofthe x, y, and z directions.